




"""simple docstring"""




import math
from collections.abc import Callable



def        a__					(							snake_case__			,					snake_case__			,					snake_case__							)		->   float:
			lowerCamelCase      =   xa
			lowerCamelCase      =   xa
			while True:
						if x_n == x_na or function(snake_case__							) == function(snake_case__							):
									raise ZeroDivisionError("""float division by zero, could not find root"""							)
						lowerCamelCase      =   x_na - (
						    function(snake_case__							) / ((function(snake_case__							) - function(snake_case__							)) / (x_na - x_n))
						)
						if abs(x_na - x_na							) < 10**-5:
									return x_na
						lowerCamelCase      =   x_na
						lowerCamelCase      =   x_na



def        a__					(							snake_case__							)		->   float:
			return math.pow(snake_case__			,					3							) - (2 * x) - 5


if __name__ == "__main__":
					print(intersection(f, 3, 3.5))









"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowerCAmelCase				:     Optional[int]					=				{"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase				:     int					=				[
					    """SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """SwinForImageClassification""",
					    """SwinForMaskedImageModeling""",
					    """SwinModel""",
					    """SwinPreTrainedModel""",
					    """SwinBackbone""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase				:     str					=				[
					    """TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFSwinForImageClassification""",
					    """TFSwinForMaskedImageModeling""",
					    """TFSwinModel""",
					    """TFSwinPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_swin import (
										    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SwinBackbone,
										    SwinForImageClassification,
										    SwinForMaskedImageModeling,
										    SwinModel,
										    SwinPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_swin import (
										    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFSwinForImageClassification,
										    TFSwinForMaskedImageModeling,
										    TFSwinModel,
										    TFSwinPreTrainedModel,
										)

else:
					import sys

					lowerCAmelCase				:     int					=				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



